1. The null hypothesis

a. Is a statement about the value of the population parameter.

b. Will always contain the equal sign.

c. Cannot include values less than 0.

d. Both a and b are correct

2. The alternate hypothesis

a. Is accepted if the null hypothesis is rejected

b. Will always contain the equal sign

c. Tells the value of the sample mean

d. None of the above

3. The level of significance

a. Is frequently .05 or .01

b. Can be any value between 0 and 1

c. Is the likelihood of rejecting the null hypothesis when it is true

d. All of the above

4. A tType I error is

a. The correct decision.

b. A value determined from the test statistic.

c. Rejecting the null hypothesis when it is true.

d. Accepting the null hypothesis when it is false.

5. The critical value is

a. Is cCalculated from sample information.

b. Cannot be negative.

c. Is tThe point that divides the acceptance region from the rejection region.

d. Is aA value determined from the test statistic.

6. In a one-tailed test

a. The rejection region is in only one of the tails.

b. The rejection region is split between the tails.

c. The p-value is always less than the significance level.

d. The p-value is always more than the significance level.

7. To conduct a one sample test of means and use the z distribution as the test statistic

a. We need to know the population mean.

b. We need to know the population standard deviation.

c. We need n  to be less than 5.

d. Both a and b are correct.

8. A p-value is

a. The same as the population proportion

b. The same as the significance level 

c. The fraction of the population that has a particular characteristic

d. The probability of finding a value of the test statistic this extreme when the null hypothesis is true

9. A Type II error occurs when

a. We accept a false null hypothesis.

b. We reject a true alternate hypothesis.

c. We reject a false null hypothesis.

d. None of the above.

10.  In hypothesis testing, whatever we are investigating or researching is specified as:

a. The null hypothesis

b. The alternative hypothesis

c. Either the null or theand alternative

d. The p-value

11. A professor of statistics refutes the claim that the average student spends 3 hours studying for the midterm exam.  Which hypothesis is used to test the claim?

a. H0: µ≠3 vs. H1: µ>3

b. H0: µ=3 vs. H1: µ≠3

c. H0: µ≠3 vs. H1: µ=3

d. H0: µ=3 vs. H1: µ<3

12.  In a criminal trial, a Type I error is made when:

a. A guilty defendant is acquitted.

b. An innocent person is convicted.

c. A guilty defendant is convicted.

d. An innocent person is acquitted

13.  In a criminal trial, a Type II error is made when:

a. A guilty defendant is acquitted.

b. An innocent person is convicted.

c. A guilty defendant is convicted.

d. An innocent person is acquitted

14.  Which of the following would be an appropriate null hypothesis?

a. The mean of a population is equal to 60.

b. The mean of a sample is equal to 60.

c. The mean of a population is not equal to 60.

d. All of the above.

15.  In order to determine the p-value, which of the following is not needded?

a. The level of significance.

b. Whether the test is one or two tail.

c. The value of the test statistic.

d. All of the above.

16.  In testing the hypothesis H0: µ=75 vs. H1: µ<75, if the value of the test statistic z equals -2.42, then the p-value is:

a. 0.5078

b. 2.420

c. 0.9922

d. 0.0078

17.  If we reject the null hypothesis, we conclude that:

a. There is enough statistical evidence to infer that the alternative hypothesis is true.

b. There is not enough statistical evidence to infer that the alternative hypothesis is true.

c. There is enough statistical evidence to infer that the null hypothesis is true.

d. The test is statistically insignificant at whatever level of significance the test was conducted. 

18.  If the value of the sample mean   is close enough to the hypothesized value µ0 of the population mean µ, then:

a. µ0 is definitely true.

b. µ0 is definitely false.

c. we rejected the null hypothesis.

d. we don't reject the null hypothesis.

19.  A numerical quantity that is computed from the data of a sample and is used in reaching a decision on whether or not to reject the null hypothesis is referred to as:

a. Significance level.

b. Critical value.

c. Test statistic.

d. Parameter

20.  We cannot commit a Type I error when the:

a. Null hypothesis is true.

b. Level of significance is 0.10.

c. Null hypothesis is false.

d. Test is a two-tail test.

21.  The level of significance can be:

a. Any value between -1.0 and 1.0

b. Any positive value

c. Anyt value smaller than 1.645

d. None of the above

22.  A spouse stated that the average amount of money spent on Christmas gifts for immediate family members is above $1,200. The correct set of hypothesis is:

a. H0: µ=200 vs. H1: µ<200

b. H0: µ>200 vs. H1: µ=200

c. H0: µ=200 vs. H1: µ>200

d. H0: µ<200 vs. H1: µ=200

23.  For a given level of significance, if the sample size n is increased, the probability of a Type I error:

a. Will decrease

b. Will increase

c. Will remain the same

d. Cannot be determined

24. If the Type I error for a given test is to be decreased, then for a fixed sample size n:

a. The Type II error will also decrease.

b. The Type II error will increase.

c. The power of the test will increase.

d. A one-tailed test must be utilized.

25.  The Type II error is committed when:

a. We reject a null hypothesis that is true.

b. We don't reject a null hypothesis that is true.

c. We reject a null hypothesis that is false.

d. We don't reject a null hypothesis that is false.